• Journal of the Korean Magnetic Resonance Society
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• v.25 no.1
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• pp.1-7
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• 2021

Employing of 13C stable-isotopes in NMR metabolomics can give unique splitting patterns and coupling constants information originated from 13C-13C coupling interaction that provide an important structural information regarding the cellular metabolic process. But it has been known that an undesirable signal distortion in 2D heteronuclear correlation study, due to 13C-13C interaction, hampers an analysis of the coupling information. Recently, we proposed J-scaled distortion-free heteronuclear single-quantum coherence (HSQC) sequence which provides a distortion-free 13C-13C coupling information with a selective resolution enhancement of JCC splitting. In this paper, we dicuss theoretical aspect and practical feature of J-scaled HSQC pulse sequence. The conceptual explanation of orgin of the signal distortion by 13C-13C coupling interaction and design of J-scaled HSQC through exemplified results are provided in brief.

• The KIPS Transactions:PartB
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• v.11B no.1
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• pp.53-62
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• 2004

The processing of emotional information is very important in Human-Computer Interaction (HCI). In particular, it is very important in video information processing to deal with a user's affection. To handle emotional information, it is necessary to represent meaningful features and detect them efficiently. Even though it is not an easy task to detect emotional events from low level features such as colour and motion, it is possible to detect them if we use statistical analysis like Linear Discriminant Analysis (LDA). In this paper, we propose a representation scheme for emotion-related features and a defection method. We experiment with extracted features from video to detect emotional events and obtain desirable results.

• The Bulletin of The Korean Astronomical Society
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• v.44 no.1
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• pp.46.3-46.3
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• 2019

We present our observational and theoretical investigation of Raman-scattered features in symbiotic stars (SySts). SySts are long interacting binaries, consisting of a hot compact star and an evolved giant, whose interaction via accretion process is at the origin of a tangled network of gas and dust nebulae. These systems are ideal objects to study a variety of important astrophysical problems, and have also been proposed as possible progenitors of type Ia supernova. In this talk, we emphasize that Raman-scattered features are exclusive spectroscopic tools to probe the stellar wind accretion processes in SySts. We studied mass transfer and mass loss processes in SySts using high resolution spectra obtained with 1.8m telescope at Mt. Bohyun and the 6.5m Magellan-Clay telescope combining with the theoretical modeling of radiative transfer of Raman-scattered features. We also note that there are a much smaller number of SySts known in our Galaxy, implying the necessity of systematic search programs. In view of the fact that Raman O VI features at $6830{\AA}$ are found in only bona fide SySts, we will carry out a photometric search of objects with Raman O VI features using a narrow band filter centered at $6830{\AA}$ in Local group galaxies.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.10
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• pp.3390-3405
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• 2022

Long Short-Term Memory (LSTM) combined with attention mechanism is extensively used to generate semantic sentences of images in image captioning models. However, features of salient regions and spatial information are not utilized sufficiently in most related works. Meanwhile, the LSTM also suffers from the problem of underutilized information in a single time step. In the paper, two innovative approaches are proposed to solve these problems. First, the Synergy-Gated Attention (SGA) method is proposed, which can process the spatial features and the salient region features of given images simultaneously. SGA establishes a gated mechanism through the global features to guide the interaction of information between these two features. Then, the Recurrent Fusion LSTM (RF-LSTM) mechanism is proposed, which can predict the next hidden vectors in one time step and improve linguistic coherence by fusing future information. Experimental results on the benchmark dataset of MSCOCO show that compared with the state-of-the-art methods, the proposed method can improve the performance of image captioning model, and achieve competitive performance on multiple evaluation indicators.

• International Journal of Contents
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• v.2 no.4
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• pp.1-7
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• 2006

The goal of Ambient Intelligence (AmI) is to build a smart environment for users where they are supported in some of their activities by many interaction mechanisms. The diversity of AmI characteristics requires special support from Operating Systems (OSes). In this paper, in order to support a conscious choice of an operating system for any specific AmI application, features requested by AmI systems were characterized and defined considering various applications. Then, characteristics of existing Operating Systems have been investigated in the context of AmI application support to relate their key characteristics to the typical requirements of AmI systems. Qualitative mapping table between AmI characteristics and as features has been proposed with an illustration of how to use it. As no as completely covers the range of characteristics required by AmI systems, challenging issues are summarized for the development of a new as and a product line of OSes.

• Korean Institute of Interior Design Journal
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• no.34
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• pp.37-44
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• 2002

In the latter half of the 20th century, the rapid change into the information society changes the concept of workplace. Especially the new types of office space are appearing to accept interaction and flexibility, which are the representative features of the information society. Therefore, this study is to suggest the appropriate office environment in the information society shifting from the territorial to the virtual, after analyzing the characteristics of space and design method for the Chiat/Day advertising agency in New York (1995) that was designed by Gaetano Pesce. As a result, in terms of the constitution and the arrangement of space, the non-territorial and the virtual features appear, and in terms of the analysis of design elements, in which various semantic connotations are used, horizontal, pluralistic, and fluid features appear. This kind of analysis would be helpful in finding new alternatives for the rapidly changing office environment.

• Journal of Computing Science and Engineering
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• v.10 no.4
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• pp.103-110
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• 2016

Emotion recognition is an important component of affective computing, and is significant in the implementation of natural and friendly human-computer interaction. An effective approach to recognizing emotion from text is based on a machine learning technique, which deals with emotion recognition as a classification problem. However, in emotion recognition, the texts involved are usually very short, leaving a very large, sparse feature space, which decreases the performance of emotion classification. This paper proposes to resolve the problem of feature sparseness, and largely improve the emotion recognition performance from short texts by doing the following: representing short texts with word cluster features, offering a novel word clustering algorithm, and using a new feature weighting scheme. Emotion classification experiments were performed with different features and weighting schemes on a publicly available dataset. The experimental results suggest that the word cluster features and the proposed weighting scheme can partly resolve problems with feature sparseness and emotion recognition performance.

• English Language & Literature Teaching
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• v.18 no.3
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• pp.53-75
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• 2012

The present study examined the role of language proficiency in dyadic discourse in the organization of repairs and the distribution of linguistic features contained in repairs. One native speaker of English and five non-native speakers participated and formed three dyads: one same-proficiency NNS-NNS (non-native speaker), one different-proficiency NNS-NNS, and one NS (native speaker)-NNS dyads. Results showed that overall repair patterns in this type of interaction were more conversational than didactic, and that the degree of difference in proficiency between the participants in the dyad influenced repair patterns and the distribution of linguistic features in relation to repair patterns. Also, discussed in the present paper are some implications of the results and other issues related to language learning.

• The Bulletin of The Korean Astronomical Society
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• v.36 no.1
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• pp.50.2-50.2
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• 2011

It is believed that active galactic nuclei (AGN) is powered by super massive black hole (SMBH). But how the AGN activity is triggered is still unclear. Some studies suggest that gas inflow by merging can trigger AGN activity. However, it is difficult to find observational evidence because merging features such as tidal tail, shell are faint. Using images taken at Maidanak 1.5m telescope and CFHT, we investigated whether merging features are seen commonly on AGN host galaxies. We found that 3 to 4 of the currently studied 6 AGN show features disturbed by gravitational interaction. This result implies that AGN activity may correlates with merging. We plan to expand the sample size in the near future.

• Korean Journal of Remote Sensing
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• v.25 no.6
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• pp.501-505
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• 2009

Quasi-linear bright features persistently appeared on ENVISAT ASAR images as well as X-SAR images along the tidal channels in Gyung-Gi Bay, Korea during the ebb tides. These features are induced by spatial backscatter variations caused by surface convergence (divergence) through the interaction between tidal currents and bathymetry. In order to validate this mechanism, a numerical tidal model simulation is performed on the realistic bathymetry with the tidal boundary conditions. The tide model reproduces the current convergence zone along the tidal channel during the ebb tides, which exactly coincides with the location of bright line features on SAR images.